Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2021
Research article |
| 22 Sep 2021
| 22 Sep 2021
A comparison of tools and techniques for stabilising unmanned aerial system (UAS) imagery for surface flow observations
Robert Ljubičić
CORRESPONDING AUTHOR
Department of Hydraulic and Environmental Engineering, Faculty of
Civil Engineering, University of Belgrade, Belgrade 11120, Serbia
Dariia Strelnikova
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Matthew T. Perks
School of Geography, Politics and Sociology, Newcastle University,
Newcastle upon Tyne NE1 7RU, United Kingdom
Anette Eltner
Institute of Photogrammetry and Remote Sensing, Technische
Universität Dresden, 01069 Dresden, Germany
Salvador Peña-Haro
Photrack AG, Ankerstrasse 16a, 8004 Zurich, Switzerland
Alonso Pizarro
Escuela de Ingeniería en Obras Civiles, Universidad Diego
Portales, 8370109 Santiago, Chile
Silvano Fortunato Dal Sasso
Department of European and Mediterranean Cultures: Architecture,
Environment and Cultural Heritage (DICEM), University of Basilicata, 75100
Matera, Italy
Ulf Scherling
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Pietro Vuono
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
Salvatore Manfreda
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B2-2026, 1183–1189, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-1183-2026, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-1183-2026, 2026
Pedro Zamboni, Robert Krüger, László Bertalan, Xabier Blanch, Paul Hindorf, and Anette Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B2-2026, 321–326, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-321-2026, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-321-2026, 2026
Carolin Rünger, Stefan Binapfl, Sophia Böhme, Ferdinand Maiwald, and Anette Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B2-2026, 261–269, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-261-2026, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-261-2026, 2026
Stefan Binapfl, Carolin Rünger, Gunnar Lelle-Neumann, Anette Eltner, and Ferdinand Maiwald
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B1-2026, 129–136, https://doi.org/10.5194/isprs-archives-XLIX-B1-2026-129-2026, https://doi.org/10.5194/isprs-archives-XLIX-B1-2026-129-2026, 2026
Laura Camila Duran Vergara, Xabier Blanch Gorriz, Bindusara Nagathihalli Lokesh, and Anette Eltner
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-2-2026, 615–622, https://doi.org/10.5194/isprs-annals-XI-2-2026-615-2026, https://doi.org/10.5194/isprs-annals-XI-2-2026-615-2026, 2026
Lea Epple, Oliver Grothum, Anne Bienert, and Anette Eltner
Earth Syst. Sci. Data, 18, 1275–1286, https://doi.org/10.5194/essd-18-1275-2026, https://doi.org/10.5194/essd-18-1275-2026, 2026
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The present study offers a unique, nested, high-resolution dataset that captures soil surface changes every 20 seconds during rainfall events, as well as over seasonal variations, across a range of spatial scales – plot, slope, and catchment. It was collected over a period of 3.5 years and facilitated by a camera-based approach. This open-access resource assists scientists in evaluating and refining existing models, improving process understanding, and training artificial intelligence.
Xabier Blanch, Jens Grundmann, Ralf Hedel, and Anette Eltner
Hydrol. Earth Syst. Sci., 30, 797–824, https://doi.org/10.5194/hess-30-797-2026, https://doi.org/10.5194/hess-30-797-2026, 2026
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This study presents a low-cost, automated system for monitoring river water levels using cameras and AI. By combining AI-based image analysis with photogrammetry, it accurately measures water levels in real-time, even in challenging conditions. Tested over 2.5 years at four sites, it achieved high accuracy (errors of 1.0–2.3 cm) and processed over 219 000 images. Its resilience makes it ideal for flood detection and water management in remote areas.
Alonso Pizarro, Oscar Link, and Demetris Koutsoyiannis
EGUsphere, https://doi.org/10.5194/egusphere-2025-6530, https://doi.org/10.5194/egusphere-2025-6530, 2026
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We explored why bridge foundations erode over time and why floods alone do not explain this risk. Using many simulated river flows linked to a model that includes erosion and sediment refilling, we found that scour is highly variable, persistent, and only weakly linked to flood extremes. Sediment coming from upstream strongly alters erosion patterns. These results show that common design methods can misjudge risk, highlighting the need to account for uncertainty in safer bridge design.
Oliver Grothum, Lea Epple, Anne Bienert, Xabier Blanch, and Anette Eltner
SOIL, 11, 1007–1028, https://doi.org/10.5194/soil-11-1007-2025, https://doi.org/10.5194/soil-11-1007-2025, 2025
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Soil erosion threatens landscapes worldwide, and understanding how surfaces change over time is key to addressing this issue. We developed a new camera-based system that automatically captures and analyzes daily surface changes on a hillside over several years. Triggered by rain and a clock, the system showed how weather and farming impact the land. Our method offers a powerful way to monitor surface changes and can help improve predictions and solutions for soil erosion.
Felix Rocco Matzke, Tushar Jayesh Barot, Shreeja Sridharan, Nikolaus Ammann, Christoph Kessler, Hans-Gerd Maas, Frank H. P. Fitzek, and Anette Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W11-2025, 211–218, https://doi.org/10.5194/isprs-archives-XLVIII-2-W11-2025-211-2025, https://doi.org/10.5194/isprs-archives-XLVIII-2-W11-2025-211-2025, 2025
Alonso Pizarro, Demetris Koutsoyiannis, and Alberto Montanari
Hydrol. Earth Syst. Sci., 29, 4913–4928, https://doi.org/10.5194/hess-29-4913-2025, https://doi.org/10.5194/hess-29-4913-2025, 2025
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We introduce the ratio of uncertainty to mutual information (RUMI), a new metric to improve rainfall-runoff simulations. RUMI better captures the link between observed and simulated stream flows by considering uncertainty at a core computation step. Tested on 99 catchments and with the GR4J model, it outperforms traditional metrics by providing more reliable and consistent results. RUMI paves the way for more accurate hydrological predictions.
Domenico Miglino, Seifeddine Jomaa, Michael Rode, Khim Cathleen Saddi, Francesco Isgrò, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 29, 4133–4151, https://doi.org/10.5194/hess-29-4133-2025, https://doi.org/10.5194/hess-29-4133-2025, 2025
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Turbidity is a key factor for water quality monitoring. Here, an image-based procedure is tested in a full-scale river monitoring experiment using digital cameras. This approach can enhance our understanding of the real-time status of waterbodies, overcoming the spatial and temporal resolution limitations of existing methods. It also facilitates early-warning systems, advances water research through increased data availability and reduces operating costs.
Matthew T. Perks, Borbála Hortobágyi, Nick Everard, Susan Manson, Juliet Rowland, Andrew Large, and Andrew J. Russell
Hydrol. Earth Syst. Sci., 29, 3727–3743, https://doi.org/10.5194/hess-29-3727-2025, https://doi.org/10.5194/hess-29-3727-2025, 2025
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Accurate river flow measurements are essential for understanding river processes. This study evaluates the freely available software KLT-IV for automatic river surface velocity measurement. Analysing over 11 000 videos and comparing them with 274 traditional flow measurements, we find strong correlations (r² = 0.95–0.97) between KLT-IV and traditional methods. KLT-IV effectively estimates river flow with high accuracy, making it a valuable tool for autonomous water resource management.
Hanne Hendrickx, Melanie Elias, Xabier Blanch, Reynald Delaloye, and Anette Eltner
Earth Surf. Dynam., 13, 705–721, https://doi.org/10.5194/esurf-13-705-2025, https://doi.org/10.5194/esurf-13-705-2025, 2025
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This study presents a novel AI-based method for tracking and analysing the movement of rock glaciers and landslides, key landforms in high mountain regions. By utilising time-lapse images, our approach generates detailed velocity data, uncovering movement patterns often missed by traditional methods. This cost-effective tool enhances geohazard monitoring, providing insights into environmental drivers, improving process understanding, and contributing to better safety in alpine areas.
Anette Eltner, David Favis-Mortlock, Oliver Grothum, Martin Neumann, Tomáš Laburda, and Petr Kavka
SOIL, 11, 413–434, https://doi.org/10.5194/soil-11-413-2025, https://doi.org/10.5194/soil-11-413-2025, 2025
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This study develops a new method to improve the calibration and evaluation of models that predict soil erosion by water. By using advanced imaging techniques, we can capture detailed changes in the soil surface over time. This helps improve models that forecast erosion, especially as climate change creates new and unpredictable conditions. Our findings highlight the need for more precise tools to better model erosion of our land and environment in the future.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
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The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
Robert Krüger, Xabier Blanch, Jens Grundmann, Ghazi Al-Rawas, and Anette Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W8-2024, 243–250, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-243-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-243-2024, 2024
Pedro Alberto Pereira Zamboni, Hanne Hendrickx, Dennis Sprute, Holger Flatt, Muhtasimul Islam Rushdi, Florian Brodrecht, and Anette Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W8-2024, 483–490, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-483-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-483-2024, 2024
Melanie Elias, Steffen Isfort, Anette Eltner, and Hans-Gerd Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-2-2024, 57–64, https://doi.org/10.5194/isprs-annals-X-2-2024-57-2024, https://doi.org/10.5194/isprs-annals-X-2-2024-57-2024, 2024
Robert Krüger, Pierre Karrasch, and Anette Eltner
Geosci. Instrum. Method. Data Syst., 13, 163–176, https://doi.org/10.5194/gi-13-163-2024, https://doi.org/10.5194/gi-13-163-2024, 2024
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Low-cost sensors could fill gaps in existing observation networks. To ensure data quality, the quality of the factory calibration of a given sensor has to be evaluated if the sensor is used out of the box. Here, the factory calibration of a widely used low-cost rain gauge type has been tested both in the lab (66) and in the field (20). The results of the study suggest that the calibration of this particular type should at least be checked for every sensor before being used.
O. Grothum, A. Bienert, M. Bluemlein, and A. Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 163–170, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-163-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-163-2023, 2023
Xabier Blanch, Marta Guinau, Anette Eltner, and Antonio Abellan
Nat. Hazards Earth Syst. Sci., 23, 3285–3303, https://doi.org/10.5194/nhess-23-3285-2023, https://doi.org/10.5194/nhess-23-3285-2023, 2023
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We present cost-effective photogrammetric systems for high-resolution rockfall monitoring. The paper outlines the components, assembly, and programming codes required. The systems utilize prime cameras to generate 3D models and offer comparable performance to lidar for change detection monitoring. Real-world applications highlight their potential in geohazard monitoring which enables accurate detection of pre-failure deformation and rockfalls with a high temporal resolution.
Qianqian Han, Yijian Zeng, Lijie Zhang, Calimanut-Ionut Cira, Egor Prikaziuk, Ting Duan, Chao Wang, Brigitta Szabó, Salvatore Manfreda, Ruodan Zhuang, and Bob Su
Geosci. Model Dev., 16, 5825–5845, https://doi.org/10.5194/gmd-16-5825-2023, https://doi.org/10.5194/gmd-16-5825-2023, 2023
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Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
R. Blaskow and A. Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 45–50, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-45-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-45-2023, 2023
Gernot Paulus, Dariia Strelnikova, Thomas Lutz, Karl-Heinrich Anders, Klaus Gäbler, Gerhard Lippitsch, Daniela Meier, and Stefan Eisenbach
AGILE GIScience Ser., 3, 51, https://doi.org/10.5194/agile-giss-3-51-2022, https://doi.org/10.5194/agile-giss-3-51-2022, 2022
Enrico Tubaldi, Christopher J. White, Edoardo Patelli, Stergios Aristoteles Mitoulis, Gustavo de Almeida, Jim Brown, Michael Cranston, Martin Hardman, Eftychia Koursari, Rob Lamb, Hazel McDonald, Richard Mathews, Richard Newell, Alonso Pizarro, Marta Roca, and Daniele Zonta
Nat. Hazards Earth Syst. Sci., 22, 795–812, https://doi.org/10.5194/nhess-22-795-2022, https://doi.org/10.5194/nhess-22-795-2022, 2022
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Bridges are critical infrastructure components of transport networks. A large number of these critical assets cross or are adjacent to waterways and are therefore exposed to the potentially devastating impact of floods. This paper discusses a series of issues and areas where improvements in research and practice are required in the context of risk assessment and management of bridges exposed to flood hazard, with the ultimate goal of guiding future efforts in improving bridge flood resilience.
Lea Epple, Andreas Kaiser, Marcus Schindewolf, and Anette Eltner
SOIL Discuss., https://doi.org/10.5194/soil-2021-85, https://doi.org/10.5194/soil-2021-85, 2021
Revised manuscript not accepted
Short summary
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Intensified extreme weather events due to climate change can result in changes of soil erosion. These unclear developments make an improvement of soil erosion modelling all the more important. Assuming that soil erosion models cannot keep up with the current data, this work gives an overview of 44 models, their strengths and weaknesses and discusses their potential for further development with respect to new and improved soil and soil erosion assessment techniques.
Salvatore Manfreda, Domenico Miglino, and Cinzia Albertini
Hydrol. Earth Syst. Sci., 25, 4231–4242, https://doi.org/10.5194/hess-25-4231-2021, https://doi.org/10.5194/hess-25-4231-2021, 2021
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In this work, we introduce a new theoretically derived probability distribution of the outflows of in-line detention dams. The method may be used to evaluate the impact of detention dams on flood occurrences and attenuation of floods. This may help and support risk management planning and design.
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Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed...
